Japanese Journal of Statistics and Data Science最新文献

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Improving kernel-based nonparametric regression for circular–linear data 改进基于核的非参数循环线性回归
IF 1.3
Japanese Journal of Statistics and Data Science Pub Date : 2022-01-31 DOI: 10.1007/s42081-022-00145-3
Yasuhito Tsuruta, Masahiko Sagae
{"title":"Improving kernel-based nonparametric regression for circular–linear data","authors":"Yasuhito Tsuruta, Masahiko Sagae","doi":"10.1007/s42081-022-00145-3","DOIUrl":"https://doi.org/10.1007/s42081-022-00145-3","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"5 1","pages":"111 - 131"},"PeriodicalIF":1.3,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"53297295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Bayesian fused lasso modeling via horseshoe prior 基于马蹄先验的贝叶斯融合套索建模
IF 1.3
Japanese Journal of Statistics and Data Science Pub Date : 2022-01-20 DOI: 10.1007/s42081-023-00213-2
Yuko Kakikawa, Kaito Shimamura, Shuichi Kawano
{"title":"Bayesian fused lasso modeling via horseshoe prior","authors":"Yuko Kakikawa, Kaito Shimamura, Shuichi Kawano","doi":"10.1007/s42081-023-00213-2","DOIUrl":"https://doi.org/10.1007/s42081-023-00213-2","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2022-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42997566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Least-squares estimators based on the Adams method for stochastic differential equations with small Lévy noise 基于Adams方法的小Lévy噪声随机微分方程的最小二乘估计
IF 1.3
Japanese Journal of Statistics and Data Science Pub Date : 2022-01-18 DOI: 10.1007/s42081-022-00155-1
Mitsuki Kobayashi, Y. Shimizu
{"title":"Least-squares estimators based on the Adams method for stochastic differential equations with small Lévy noise","authors":"Mitsuki Kobayashi, Y. Shimizu","doi":"10.1007/s42081-022-00155-1","DOIUrl":"https://doi.org/10.1007/s42081-022-00155-1","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"5 1","pages":"217 - 240"},"PeriodicalIF":1.3,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48900408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Inferences on cumulative incidence function for middle censored survival data with Weibull regression 用威布尔回归对中间截尾生存数据累积关联函数的推断
IF 1.3
Japanese Journal of Statistics and Data Science Pub Date : 2022-01-14 DOI: 10.1007/s42081-021-00142-y
H. Rehman, N. Chandra
{"title":"Inferences on cumulative incidence function for middle censored survival data with Weibull regression","authors":"H. Rehman, N. Chandra","doi":"10.1007/s42081-021-00142-y","DOIUrl":"https://doi.org/10.1007/s42081-021-00142-y","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"5 1","pages":"65 - 86"},"PeriodicalIF":1.3,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"53297203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Spatial analysis of subjective well-being in Japan 日本主观幸福感的空间分析
IF 1.3
Japanese Journal of Statistics and Data Science Pub Date : 2022-01-06 DOI: 10.1007/s42081-021-00143-x
Anqi Li, Takaki Sato, Y. Matsuda
{"title":"Spatial analysis of subjective well-being in Japan","authors":"Anqi Li, Takaki Sato, Y. Matsuda","doi":"10.1007/s42081-021-00143-x","DOIUrl":"https://doi.org/10.1007/s42081-021-00143-x","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"5 1","pages":"87 - 110"},"PeriodicalIF":1.3,"publicationDate":"2022-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49371693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Exploring the impact of air pollution on COVID-19 admitted cases: Evidence from vector error correction model (VECM) approach in explaining the relationship between air pollutants towards COVID-19 cases in Kuwait. 探索空气污染对COVID-19入院病例的影响:来自矢量误差修正模型(VECM)方法的证据,用于解释科威特空气污染物与COVID-19病例之间的关系。
IF 1.3
Japanese Journal of Statistics and Data Science Pub Date : 2022-01-01 Epub Date: 2022-06-28 DOI: 10.1007/s42081-022-00165-z
Ahmad R Alsaber, Parul Setiya, Ahmad T Al-Sultan, Jiazhu Pan
{"title":"Exploring the impact of air pollution on COVID-19 admitted cases: Evidence from vector error correction model (VECM) approach in explaining the relationship between air pollutants towards COVID-19 cases in Kuwait.","authors":"Ahmad R Alsaber,&nbsp;Parul Setiya,&nbsp;Ahmad T Al-Sultan,&nbsp;Jiazhu Pan","doi":"10.1007/s42081-022-00165-z","DOIUrl":"https://doi.org/10.1007/s42081-022-00165-z","url":null,"abstract":"<p><p>In urban areas, air pollution is one of the most serious global environmental issues. Using time-series approaches, this study looked into the validity of the relationship between air pollution and COVID-19 hospitalization. This time series research was carried out in the state of Kuwait; stationarity test, cointegration test, Granger causality and stability test, and test on multivariate time-series using the Vector Error Correction Model (VECM) technique. The findings reveal that the concentration rate of air pollutants ( <math><msub><mtext>O</mtext> <mn>3</mn></msub> </math> , <math><msub><mtext>SO</mtext> <mn>2</mn></msub> </math> , <math><msub><mtext>NO</mtext> <mn>2</mn></msub> </math> , <math><mtext>CO</mtext></math> , and <math><msub><mtext>PM</mtext> <mn>10</mn></msub> </math> ) has an effect on COVID-19 admitted cases via Granger-cause. The Granger causation test shows that the concentration rate of air pollutants ( <math><msub><mtext>O</mtext> <mn>3</mn></msub> </math> , <math><msub><mtext>PM</mtext> <mn>10</mn></msub> </math> , <math><msub><mtext>NO</mtext> <mn>2</mn></msub> </math> , temperature and wind speed) influences and predicts the COVID-19 admitted cases. The findings suggest that sulfur dioxide ( <math><msub><mtext>SO</mtext> <mn>2</mn></msub> </math> ), <math><msub><mtext>NO</mtext> <mn>2</mn></msub> </math> , temperature, and wind speed induce an increase in COVID-19 admitted cases in the short term according to VECM analysis. The evidence of a positive long-run association between COVID-19 admitted cases and environmental air pollution might be shown in the cointegration test and the VECM. There is an affirmation that the usage of air pollutants ( <math><msub><mtext>O</mtext> <mn>3</mn></msub> </math> , <math><msub><mtext>SO</mtext> <mn>2</mn></msub> </math> , <math><msub><mtext>NO</mtext> <mn>2</mn></msub> </math> , <math><mtext>CO</mtext></math> , and <math><msub><mtext>PM</mtext> <mn>10</mn></msub> </math> ) has a significant impact on COVID-19-admitted cases' prediction and its explained about 24% of increasing COVID-19 admitted cases in Kuwait.</p>","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":" ","pages":"379-406"},"PeriodicalIF":1.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9244511/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40482917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Shiga University's endeavor to promote human resources development for data science in Japan. 滋贺大学致力于促进日本数据科学领域的人力资源开发
IF 1.1
Japanese Journal of Statistics and Data Science Pub Date : 2022-01-01 Epub Date: 2022-03-27 DOI: 10.1007/s42081-022-00151-5
Takuma Tanaka, Tetsuto Himeno, Kaoru Fueda
{"title":"Shiga University's endeavor to promote human resources development for data science in Japan.","authors":"Takuma Tanaka, Tetsuto Himeno, Kaoru Fueda","doi":"10.1007/s42081-022-00151-5","DOIUrl":"10.1007/s42081-022-00151-5","url":null,"abstract":"<p><p>In 2017, Shiga University established the Faculty of Data Science, which was the first faculty in Japan specializing in data science and statistics. This paper reports the Faculty's historical context, curricula, and collaboration with industry and other universities. The career paths of the graduates and the massive open online courses and textbooks provided by the Faculty of Data Science are also summarized.</p>","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"5 1","pages":"747-755"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8958343/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43496285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Determination of optimal prevention strategy for COVID-19 based on multi-agent simulation. 基于多智能体仿真的COVID-19最优预防策略确定
IF 1.3
Japanese Journal of Statistics and Data Science Pub Date : 2022-01-01 Epub Date: 2022-06-14 DOI: 10.1007/s42081-022-00163-1
Satoki Fujita, Ryo Kiguchi, Yuki Yoshida, Yoshitake Kitanishi
{"title":"Determination of optimal prevention strategy for COVID-19 based on multi-agent simulation.","authors":"Satoki Fujita,&nbsp;Ryo Kiguchi,&nbsp;Yuki Yoshida,&nbsp;Yoshitake Kitanishi","doi":"10.1007/s42081-022-00163-1","DOIUrl":"https://doi.org/10.1007/s42081-022-00163-1","url":null,"abstract":"<p><p>This study proposes a direction for the utilization of multi-agent simulation (MAS) to consider an optimal prevention strategy for the spread of the coronavirus disease of 2019 (COVID-19) through a pandemic modeling example in Japan. MAS can flexibly express macroscopic phenomena formed through the interaction of micro-agents modeled to act autonomously. The use of MAS can provide a variety of recommendations for bringing a pandemic under control, even in the case of the COVID-19 pandemic, which has become more intense as of 2021. However, models that do not consider individual heterogeneity, such as analytical Susceptible-Exposed-Infectious-Recovered (SEIR) models, are often used as predictive models for infectious diseases and the main reference for decision-making. In this study, we show that by constructing a MAS that simulates a metropolitan city in Japan in a simple manner while considering the heterogeneity of age and other background information, we can capture the effects of various measures such as vaccinations on the spread of infections in a more realistic setting. Moreover, it is possible to offer various recommendations for optimal strategies to suppress a pandemic by combining reinforcement learning with MAS. This study explicates the potential of MAS in the development of strategies to prevent the spread of infection.</p>","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":" ","pages":"339-361"},"PeriodicalIF":1.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9195403/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40164743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Special feature: statistics for COVID-19 pandemic data. 专题:新冠肺炎疫情数据统计
IF 1.1
Japanese Journal of Statistics and Data Science Pub Date : 2022-01-01 Epub Date: 2022-06-02 DOI: 10.1007/s42081-022-00166-y
Koji Kurihara
{"title":"Special feature: statistics for COVID-19 pandemic data.","authors":"Koji Kurihara","doi":"10.1007/s42081-022-00166-y","DOIUrl":"10.1007/s42081-022-00166-y","url":null,"abstract":"","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":"5 1","pages":"275-277"},"PeriodicalIF":1.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9161758/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48638092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Correction to: Exploring the impact of air pollution on COVID-19 admitted cases: Evidence from vector error correction model (VECM) approach in explaining the relationship between air pollutants towards COVID-19 cases in Kuwait. 修正:探索空气污染对COVID-19入院病例的影响:来自矢量误差校正模型(VECM)方法的证据,用于解释科威特空气污染物与COVID-19病例之间的关系。
IF 1.3
Japanese Journal of Statistics and Data Science Pub Date : 2022-01-01 Epub Date: 2022-08-18 DOI: 10.1007/s42081-022-00174-y
Ahmad R Alsaber, Parul Setiya, Ahmad T Al-Sultan, Jiazhu Pan
{"title":"Correction to: Exploring the impact of air pollution on COVID-19 admitted cases: Evidence from vector error correction model (VECM) approach in explaining the relationship between air pollutants towards COVID-19 cases in Kuwait.","authors":"Ahmad R Alsaber,&nbsp;Parul Setiya,&nbsp;Ahmad T Al-Sultan,&nbsp;Jiazhu Pan","doi":"10.1007/s42081-022-00174-y","DOIUrl":"https://doi.org/10.1007/s42081-022-00174-y","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1007/s42081-022-00165-z.].</p>","PeriodicalId":29911,"journal":{"name":"Japanese Journal of Statistics and Data Science","volume":" ","pages":"719-720"},"PeriodicalIF":1.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9387877/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40421570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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